Robust image hashing based on random Gabor filtering and dithered lattice vector quantization
In this paper, we propose a robust-hash function based on random Gabor filtering and dithered lattice vector quantization (LVQ). In order to enhance the robustness against rotation manipulations, the conventional Gabor filter is adapted to be rotation invariant, and the rotation-invariant filter is...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/84794 http://hdl.handle.net/10220/13476 |
| _version_ | 1826115914226991104 |
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| author | Li, Yuenan. Lu, Zheming. Zhu, Ce. Niu, Xiamu. |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Li, Yuenan. Lu, Zheming. Zhu, Ce. Niu, Xiamu. |
| author_sort | Li, Yuenan. |
| collection | NTU |
| description | In this paper, we propose a robust-hash function based on random Gabor filtering and dithered lattice vector quantization (LVQ). In order to enhance the robustness against rotation manipulations, the conventional Gabor filter is adapted to be rotation invariant, and the rotation-invariant filter is randomized to facilitate secure feature extraction. Particularly, a novel dithered-LVQ-based quantization scheme is proposed for robust hashing. The dithered-LVQ-based quantization scheme is well suited for robust hashing with several desirable features, including better tradeoff between robustness and discrimination, higher randomness, and secrecy, which are validated by analytical and experimental results. The performance of the proposed hashing algorithm is evaluated over a test image database under various content-preserving manipulations. The proposed hashing algorithm shows superior robustness and discrimination performance compared with other state-of-the-art algorithms, particularly in the robustness against rotations (of large degrees). |
| first_indexed | 2024-10-01T04:02:54Z |
| format | Journal Article |
| id | ntu-10356/84794 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:02:54Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/847942020-03-07T13:57:29Z Robust image hashing based on random Gabor filtering and dithered lattice vector quantization Li, Yuenan. Lu, Zheming. Zhu, Ce. Niu, Xiamu. School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering In this paper, we propose a robust-hash function based on random Gabor filtering and dithered lattice vector quantization (LVQ). In order to enhance the robustness against rotation manipulations, the conventional Gabor filter is adapted to be rotation invariant, and the rotation-invariant filter is randomized to facilitate secure feature extraction. Particularly, a novel dithered-LVQ-based quantization scheme is proposed for robust hashing. The dithered-LVQ-based quantization scheme is well suited for robust hashing with several desirable features, including better tradeoff between robustness and discrimination, higher randomness, and secrecy, which are validated by analytical and experimental results. The performance of the proposed hashing algorithm is evaluated over a test image database under various content-preserving manipulations. The proposed hashing algorithm shows superior robustness and discrimination performance compared with other state-of-the-art algorithms, particularly in the robustness against rotations (of large degrees). 2013-09-16T06:13:08Z 2019-12-06T15:51:14Z 2013-09-16T06:13:08Z 2019-12-06T15:51:14Z 2011 2011 Journal Article Li, Y., Lu, Z., Zhu, C. & Niu, X. (2011). Robust Image Hashing Based on Random Gabor Filtering and Dithered Lattice Vector Quantization. IEEE Transactions on Image Processing, 21(4), 1963-1980. 1057-7149 https://hdl.handle.net/10356/84794 http://hdl.handle.net/10220/13476 10.1109/TIP.2011.2171698 en IEEE transactions on image processing © 2011 IEEE |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering Li, Yuenan. Lu, Zheming. Zhu, Ce. Niu, Xiamu. Robust image hashing based on random Gabor filtering and dithered lattice vector quantization |
| title | Robust image hashing based on random Gabor filtering and dithered lattice vector quantization |
| title_full | Robust image hashing based on random Gabor filtering and dithered lattice vector quantization |
| title_fullStr | Robust image hashing based on random Gabor filtering and dithered lattice vector quantization |
| title_full_unstemmed | Robust image hashing based on random Gabor filtering and dithered lattice vector quantization |
| title_short | Robust image hashing based on random Gabor filtering and dithered lattice vector quantization |
| title_sort | robust image hashing based on random gabor filtering and dithered lattice vector quantization |
| topic | DRNTU::Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/84794 http://hdl.handle.net/10220/13476 |
| work_keys_str_mv | AT liyuenan robustimagehashingbasedonrandomgaborfilteringandditheredlatticevectorquantization AT luzheming robustimagehashingbasedonrandomgaborfilteringandditheredlatticevectorquantization AT zhuce robustimagehashingbasedonrandomgaborfilteringandditheredlatticevectorquantization AT niuxiamu robustimagehashingbasedonrandomgaborfilteringandditheredlatticevectorquantization |